代码是这样的
clc;clear all;
p=(3695,6060,96.3;
3695,6060,95.8;
3695,6060,95.2;
3662,6060,96.2;
3390,6060,96.7;
3117,6060,97.5;
3176,6060,96.7;
3235,6060,97.3;
3294,6060,97;
3343,6560,96.5;
3391,6560,96;
3440,6560,96.9;
3755,6560,95.6;
4071,6560,94.3;
4386,6560,94.5;
3050,6560,94;
1715,6560,94.3;
379,6560,94.1;
1519,7560,94.5;
2660,7560,93.7;
3800,7560,93.4;
3839,7560,92.4;
3877,7560,90.2;
3916,6660,88.7;
4222,6520,86.8;
4528,6520,86.5;
4834,6810,86;
4563,6810,86.1;
4293,6810,86.7;
4022,7210,86.5;
4054,7810,87.5;
4085,7590,88;
4117,7890,88.1;
4145,7890,87.5;
4174,8370,88.6;
4202,8370,103.9;
4571,8370,104.7;
4939,8370,104.2;
5308,8370,107.9;
5022,8690,106.6;
4735,8690,108;
4449,8460,108.9;
4491,8460,107.8;
4534,8460,107.3;
4576,8460,104.4;
4643,8460,103.8;
4709,8690,102.9;
4776,9000,100.4;
5172,9000,99.9;
5567,9350,99.6;
5963,9350,107.6;
5668,9850,106.6;
5373,9850,105.8;
5078,9850,108.1;
5139,9850,105.6;
5199,9850,105;
5260,9850,103.4;
5509,9550,100.5;
5509,9550,97;
5509,9550,100.5;)
t=(552518;417651 ;567000 ;545824 ;488490 ;511934 ;457162 ;481342;560976;496928;582750;635346;649045;488864;700505;604920;564637;588361;488219;451299;552808;538457;522843;584609;610596;607299;772353;830974;829071;872894;832596;858278;1015069;946463;1036422;1103348;1315990;942942;1264958;1110874;1043220;1042818;946172;1018977;1211428;1203174;1339756;1308575;1528965;967242;1347659;1145320;1042863;1109210;1011842;1095170;1319502;1220779;1343668;1368891)
p = p'; t = t';
%利用premnmx函数对数据进行归一化
[pn,minp,maxp,tn,mint,maxt]=premnmx(p,t); % 对于输入矩阵p和输出矩阵t进行归一化处理
dx=[-1,1]; %归一化处理后最小值为-1,最大值为1
net=newff(minmax(pn),[5,1],{'logsig', 'purelin'},'trainlm'); % 建BP网络
inputWeights=net.IW{1,1};
inputbias=net.b{1};
layerWeights=net.IW{1,1};
layerbias=net.b{2};
nParam.show=50; %50次显示一次结果
net.trainParam.Lr=0.05; %学习速度为0.05
net.trainParam.epochs=10000; %最大训练10000次
net.trainParam.goal=0.0001; %均方误差
net=train(net,pn,tn); %开始训练,其中pn,tn分别为输入输出样本
an=sim(net,pn); %用训练好的模型进行仿真
p_test=(6796,9559,103.9;
6796,9850,105;
6796,9850,105;
6796,10450,100.1;
6435,10450,103;
6074,10120,104.2;
5713,9590,99.3;
5781,9170,98.2;
849,9560,99.4;
5918,10110,100.8;
5991,10110,106.1;
6064,9810,105.1;
6138,9810,103.7;)
p_test = p_test';
pn_test=tramnmx(p_test,minp,maxp);
%利用原始数据对BP网络仿真
a=postmnmx(an,mint,maxt); % 把仿真得到的数据还原为原始的数量级;
tn_test=sim(net,pn_test);
t_test=postmnmx(tn_test,mint,maxt);但是出现了下面的问题
??? p=(3695,6060,96.3;
|
Error: Incomplete or misformed expression or statement.
>>
要怎么解决呢


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